Precision Health Retailing: How Big Data and Artificial Intelligence May Accelerate Success for Pulse-Based Food Convergent Innovation
By Laurette Dubé, Bob Chapman, Jian Yun Nie & Shawn T. Brown
In an earlier article from the convergent innovation series, we reported that recent advances in the family of “omics” technologies have enabled the new sectors of precision food and precision nutrition, i.e., the tailoring of food and diet to specific individual biological predispositions that impact health and diseases (Prakash, Bacon, & Dubé, 2017). Similar technologies have even a longer history in precision medicine (Hizel, Tremblay, Bartlett, & Hamet, 2017), i.e., the tailoring of disease management as a function of molecular-level information on one or the other facets of a patient’s biology. Big data and artificial intelligence are also extensively used, not only in the biological sphere, but as tools by businesses for accurate and real-time targeting of consumers; thus, fueling the simultaneous alignment of supply and demand with business strategy and operation. As a core capability of convergent innovation, we propose precision health retailing as a next frontier to accelerate what big data and artificial intelligence can contribute through food to improving population health, containing healthcare costs, and contributing to economic performance and growth of the agri-food sector. Pulses are perfect test beds to explore such possibilities.
The growing global production and utilization of pulses as affordable commodities that are naturally good for the health of people and planet, offers an idea with great potential for break-through innovation. Artificial intelligence and big data will significantly boost societal impacts in food and health by bridging the many silos of science, technologies and consumer insights needed to create more targeted food innovation. This future food is located at the converging point where it is at the same time: what consumers want; what they need for their vitality and health; what they can and want to pay; what the planet can offer in a sustainable way; and what the agriculture and food sectors can and want to produce in a cost-effective and profitable manner. Creating an adequate supply and demand for this 21st century food requires transforming both our methods of innovation as well as the current practices of a broad spectrum of stakeholders, including consumers.
In a society entering the 4th industrial revolution with no clear boundaries between the biological, physical, and digital spheres, retail is a gateway where individuals intersect with larger systems and organizations in agriculture, food, health, and other social and economic sectors impacting their choice. Powered by advanced digital platforms and infrastructure with leading scientific knowledge on the drivers of human behavior in varying contexts, Precision Health Retailing (PHR) will modernize food commercialization by providing deep insights into consumer minds and industry trends.
These insights help develop, understand and balance food supply with demand, bringing together all science and technologies necessary for end-to-end solutions to successful food innovation. PHR operates at the frontiers of knowledge not only in the behavioral and social sciences but also in neuroscience, data, computer, and complexity science to develop an integrative and solution-oriented translational paradigm.
As examples of how PHR can help commercialization, consider the complexity of understanding relationships between people’s behaviors in food consumption and choice, and the systems involved in supplying the products to markets. To garner a better understanding and to provide decision makers with a tool for testing new ideas, products and policies, we are building a modular artificial intelligence-enabled digital platform to inform the design, go-to-market strategy and performance monitoring of food convergent innovation. We have started to develop a component to extract insights from user-generated content through social media (e.g. Twitter, Facebook), with a rich diversity of consumer insights on sometimes conflicting demand drivers to inform break-through innovation (Dubé, Du, McRae, Jayaraman, & Nie, 2018). Results show that positive and negative drivers of demands for food convergent innovation, as expressed in this digital social media corpus, bear on their own belief systems, experiences and culture, as well as the characteristics of the food they associate with and the expected consequences that motivate their behavior. We also are planning to build a technology we call the “virtual marketplace”.
This virtual marketplace is a computer laboratory to rapidly test new products’ marketability, ability to enhance population health, and potential strategies for enhancing both. The “virtual marketplace” can be best thought of as a SimCity for food systems, i.e. like a simulation video game, there will be virtual people that interact with each other and their environment to update their status as well as the virtual world they inhabit. We will utilize and enhance existing synthetic ecosystems (i.e. datasets that are derived from census information to provide a realistic set of people and places) of Canada including information regarding food purchasing, processing, and manufacturing location as a basis for the “virtual marketplace”. We will create simulations with rules that are derived from data and studies from other components of this work. By changing various inputs to the simulation, decision-makers can perform a number of pilot experiments in the computer before attempting them in the real world, allowing for exploration of much larger space of possibilities thus finding the most impactful solutions rapidly.
Information and digital technologies are rapidly replacing fuel and other physical resources as drivers of both social and economic change. For food, pulses are likely front-runners where artificial intelligence and other digital technology can blend the best of tradition and modernity creating balanced societies all around the world that can better afford health, wealth and wellbeing for all.
1. Prakash, J., Bacon, G., & Dubé, L. (2017, November). Pulses as Nature’s Gift for Precision Food and Precision Nutrition. Global Pulse Confederation: Pulse Pod (pp. 12-14).
2. Hizel, C., Tremblay, J., Bartlett, G., & Hamet, P. (2017). Every Individual Is Different and Precision Medicine Offers Options for Disease Control and Treatment. In Progress and Challenges in Precision Medicine (pp. 1-34).
3. Dubé L., Du, P., McRae, C., Jayaraman, S. & Nie, J.Y. (2018). Enabling Convergent Innovation Through an Artificial Intelligence Social Media Platform: The Case of Food. Technology Innovation Management Review, 8(2): 49-65. http://doi.org/10.22215/timreview/1139
Dr. Dubé is a Full Professor and holds the James McGill Chair of consumer and lifestyle psychology and marketing at the Desautels Faculty of Management of McGill University, Canada. Her research interest bears on the study of affects and behavioural economic processes underlying consumption and lifestyle behavior and how such knowledge can inspire more effective health and marketing communications in both real-life and technology-supported media. She is the Founding Chair and Scientific Director of the McGill Centre for the Convergence of Health and Economics. The MCCHE was created to foster partnerships among scientists and decision-makers from all sectors of society to encourage a more ambitious notion of what can be done for more effective health management and novel pathways for social and business innovation.
Dr. Chapman is the Principal Research Officer for the National Research Council Canada’s (NRC) Aquatic & Crop Resource Development Portfolio based out of Charlottetown, PEI. He is responsible for leading strategic projects to develop new functional ingredients including nutritional oils and alternate proteins. Dr. Chapman has been working with McGill’s Food Convergent Innovation group for the past 3 years to advance new product development projects for both large and small companies. Dr. Chapman holds a Ph.D. in Organic Chemistry from the University of British Columbia and is an Adjunct Professor with the Chemistry Department at the University of Prince Edward Island. He has published widely, holds several patents, has presented at numerous scientific symposia, and is the recipient of many awards, including a postdoctoral fellowship from the Natural Sciences and Engineering Research Council of Canada (NSERC) tenured at Harvard University. Additionally, Dr. Chapman is a member the Atlantic Veterinary College Advisory Council; the Advisory Board for the American Botanical Council; the recording secretary for ASTM D37.04; and a Board Member for both the PEI BioAlliance and the Natural Health Product Research Society where he also serves as vice-president
Dr. Jian-Yun Nie is a Professor in Computer Science at the University of Montreal, Canada, and is associated with the IVADO institute. He obtained a PhD degree from Université Joseph Fourier of Grenoble, France. He specializes in information retrieval, natural language processing, and artificial intelligence. He has been doing research in these areas for 30 years and has published many papers on these topics. He has served as general chair and PC chair for several conferences in the area of information retrieval. He is on the board of several international journals, including Information Retrieval Journal. He has been an invited researcher at several institutions (Tsinghua University, Peking University) and companies (Microsoft Research, Baidu, and Yahoo!).
Dr. Brown is the Associate Director of Research Software Development at the McGill Centre for Integrative Neuroscience at McGill University. He leads a team of developers providing infrastructure for executing reproducible, reliable computational pipelines for large-scale simulation and neuroscience on high-performance and cloud based computing platforms. He received his PhD. in Chemistry from the University of Georgia in 2001 and over the last 25 years has worked in high-performance computing, computational infrastructure and scientific simulation. Prior to joining McGill, he was the Director of Public Health Applications at the Pittsburgh Supercomputing Center at Carnegie Mellon University, Director of Computational Research at the Global Obesity Center at Johns Hopkins University, and Assistant Professor of Biostatistics at the University of Pittsburgh Graduate School of Public Health. His interests include agent-based modeling of populations, reproducibility, sharing, and publication of computation and data, and public health simulation modelling.
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